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This paper aims to provide a novel explorative perspective on fund managers’ decisions under uncertainty. The current COVID pandemic is used as a unique reference frame to study how heuristics are used in institutional financial practice.

This study follows a grounded theory approach. A total of 282 diverse publications between October 2019 and October 2020 for 20 German mutual funds are qualitatively analyzed. A theory of adaptive heuristics for fund managers is developed.

Fund managers adapt their heuristics during a crisis and this adaptive process flows through three stages. Increasing complexity in the environment leads to the adaption of simplest heuristics around investment decisions. Three distinct stages of adaption: precrisis, uncertainty and stabilization emerge from the data.

This study’s data is based on publicly available information. There might be a discrepancy between publicly stated and internal reasoning.

Money managers can use the provided framework to assess their decision-making in crises. The developed adaptive processes of heuristics can assist capital allocators who choose and rate fund managers. Policymakers and regulators can learn about the aspects of investor decisions that their actions and communication address. Teaching can use this study to exemplify the nature of financial markets as adaptive systems rather than static structures.

To the best of the author’s/authors’ knowledge, this study is the first to systematically explore the heuristics of professional money managers because they navigate a large-scale exogenous crisis.

This paper aims to explore the role of heuristics in the reassessment of relationship events and how it influences perceptions of commitment, fairness and relationship value. It answers the question of how heuristics interrelate with decision-makers’ evolving interpretations of commitment, fairness and relationship value in a specific buyer-supplier relationship.

This paper presents data from a longitudinal study of an evolving buyer–supplier relationship involving a multinational supplier of fast-moving consumer goods and a medium-sized and highly specialized supplier. It analyzes qualitative data about the use of heuristics in buyer–supplier relationships, and it is based on evidence collected from interviews, presentations, meetings and secondary data.

This paper shows that a buyer’s unexpected behavior can lead to a reassessment of commitment, fairness and relationship value. Heuristics can delay relationship reassessments, however. The case shows that heuristics have a preserving quality and that the effect of transformative events only slowly changes the perception of the value of the relationship. In this change process, the link between commitment, perceived fairness and heuristics is crucial.

This paper contributes to research on the relationship between buyer–supplier relationships and heuristics. In particular, the paper contributes to the understanding of how relational events in a buyer-supplier relationship change the commitment and perception of fairness, and how heuristics change accordingly. On a more overarching level, the study contributes to our understanding of business relationship dynamics.

The transition to a circular economy (CE) is a known concern in the context of the textile industry, in which business actors attempt to facilitate circular activities such as textile recycling. However, a lack of established business relationships and networks creates uncertainty for textile circulation. In such business environments, managerial decisions regarding CE may depend not only on normative behaviour but also on heuristics that guide their choices. Since business relationships for textile circularity require interactions between business actors, this study explores how managerial heuristics are shaped in the CE transition within the textile industry and their impact on actors’ interactions within business relationships and networks.

Empirically, this qualitative study is based on interviews with managers representing companies and organisations engaged in business relationships and networks aimed at a CE transition in the textile industry, as well as on publicly available secondary data.

The findings indicate that managerial decisions promoting circularity can be influenced by, besides normative information assessment, factors predominant in (1) the business and regulatory environment, (2) managers’ experience and knowledge obtained during interactions within business networks and (3) the internal strategic approaches of business organisations. This study identifies adaptation, experience, interaction and strategy heuristics that may be utilised by managers in making decisions in the context of uncertainty, such as the industrial transition to a CE.

This study expands the knowledge of heuristics applied to managerial decision making in interacting business firms and institutional organisations aiming to facilitate textile recycling and proposes a heuristics toolbox. The study provides an insight into business actors’ interactions, as well as various factors inside and outside the organisations shaping the managerial decisions. By doing this, the study adds to the literature, highlighting the importance of contextualisation and the interrelation between the individual and business environment levels in business-to-business management.

Most scientific research has focused on understanding Ponzi schemes from the point of view of the schemes and their operators, based on qualitative analysis. This paper aims to analyze Ponzi schemes from the perspective of their investors, emphasizing behavioral aspects, which have been little explored in the scientific literature, especially in quantitative research. In this way, the authors sought to understand the effects of heuristics and cognitive biases in understanding investor behavior.

A logistic regression was carried out with Brazilian investors, some of them participants in Ponzi schemes, who answered a structured questionnaire by means of a survey.

The authors found that social pressures, overconfidence and deliberate ignorance lead to credulity, generating little risk analysis and the desire to make a lot of money quickly.

Helping investors improve their levels of information through financial education and self-knowledge about their behavior. Contribute to the competent authorities in the search for improvements in the information displayed to investors.

Understanding the mechanisms used when making a financial decision from the point of view of investors in general, but especially those exposed to Ponzi schemes, has the mission of enlightening them about the importance of financial education and the weight of psychological factors so that they can reduce the effects of heuristics and analysis biases when faced with a financial decision.

The basis of this work will be the inclusion of psychological variables and financial education, adapting existing models in an attempt to demonstrate the effects they may or may not have on mental accounting in the specific case of investors

This study aims to investigate the impact of facial-based perceived trustworthiness on stock valuation, particularly, in the initial public offering (IPO). IPO settings provide the opportunity to investigate whether information asymmetry resulting from company newness in the market would influence the incorporation of soft information in the form of executive facial trustworthiness in stock valuation.

We use a recent machine learning algorithm to detect facial landmarks and then calculate a composite facial trustworthiness measure using several facial features that have previously been observed in neuroscience and psychological studies to be the most determining factor of perceived trustworthiness. We then regress the facial trustworthiness of IPO firm executives to IPO underpricing.

Utilizing machine learning algorithms, we find that the facial trustworthiness of the company executive negatively impacts the extent of IPO underpricing. This result implies that investors incorporate the facial trustworthiness of company executives into stock valuation. The IPO underpricing also shows that the cost of equity is higher when perceived trustworthiness is low. With regard to the higher information asymmetry in IPO transactions, such a negative impact implies the role of facial trustworthiness in alleviating information asymmetry.

This study provides evidence of the impact of top management personal characteristics on firms’ financial transactions in the Indonesian context. From the perspective of investors and other fund providers, this study shows evidence that heuristics still play an important role in financial decision-making. This is also an indication of investor reliance on soft information. Our research method also provides a new opportunity for the use of machine-learning algorithms in processing non-conventional types of data in finance research, which is still relatively rare in emerging markets like Indonesia. To the best of our knowledge, our study is the first to use personalized measures of trust generated through machine-learning algorithms in IPO settings in Indonesia.

The inherent variability on process times and demand are the factors that prevent the efficient application of lean philosophy in multi-project product development (PD) environments. Considering this variability, a hybrid push–pull project control system is developed, and value stream costing (VSC) analysis is performed to reflect the relation between project lead time, capacity and project cost. The assessment of the push/pull project control on lead time improvement and long-term savings on capacity have been aimed with the proposed complete design structure.

In a team-based structure, formed through clustering, push control techniques for planning tasks within cross-functional teams and pull control techniques for planning tasks between cross-functional teams are developed. The final step evaluates the proposed structure through VSC and long-term savings have been pointed out, especially in terms of freed-up capacity. For the validation of the proposed methodology, an office furniture manufacturing firm’s PD department has been considered and the performance of the hybrid system has been observed through simulation experiments and based on the simulation results, the lean system is evaluated by VSC.

The results of simulation experiments show a superior performance of the proposed hybrid push/pull project control mechanism under different settings of cycle time between projects or shortly project cycle time, dispatching rules within teams and variability levels. The results of the Box-Score (tool to apply VSC) indicate increased capacity in the long term to add extra projects during the planning period with the same project lead time and without additional cost.

Although extensive simulation experiments have been performed to quantify the effect of project control structure and positive results have been reported on lead time and cost, the proposed design structure has not been tested in all existing PD environments.

To the best of authors’ knowledge, the quantification of the effect of hybrid project control with VSC is the first attempt to be applied in lean PD projects.

Financial literacy, capability and behavior are crucial factors in personal financial management, which in turn plays a significant role in individual and societal financial well-being. The objective of this investigation is to explain critical factors and dimensions of personal financial management systems by employing a hybrid approach that encompasses a bibliometric analysis and a systematic review of the literature.

The research team carefully evaluated a selection of 606 scholarly articles from the Scopus database and studied the evolution of personal financial management behavior over 38 years (1986–2023). This research adopted several graphical representations and network structures to comprehend publishing tendencies, high-impact papers, theoretical frameworks, intellectual constructs as well as the current state of research collaboration.

Four major clusters were identified in the field of personal financial management behavior: the relationship between financial literacy and financial capability, factors influencing financial behavior, the impact of financial behavior on financial well-being and the financial behavior of different demographic groups. In addition, by performing content analysis on papers published within the last five years, new themes in personal financial management behavior were identified.

This investigation serves to equip financial advisors, policy architects and scholarly investigators with a deeper insight into the intricacies of personal financial management behavior and aids in pinpointing prospective domains for forthcoming research.

This study seeks to address a significant vacuum in the current body of research by providing a thorough bibliometric analysis that specifically examines financial literacy, ability and conduct. To the best of our knowledge, no previous research has conducted such a comprehensive investigation in this field. This research aims to identify important researchers and influential works in the subject by using a mixed-methods approach that combines qualitative and quantitative methodologies, including content analysis. The purpose of doing this is to provide exclusive insights and expertise that can be highly valuable to scholars, practitioners, policymakers and other stakeholders who are interested in furthering the comprehension and encouragement of financial literacy and responsible financial behavior.

Alongside its remarkable growth, problematic Bitcoin investment (BI) behavior and its associated negative consequences have become prevalent, and only a few studies have examined it. Therefore, this study aims to examine problematic BI behavior by investigating its specific antecedents and consequences and identifying which antecedents were more influential in it. In addition, we also examine the role of financial literacy on the relationship between the antecedents and problematic BI behavior.

We collected survey data from 413 investors with Bitcoin investment experience in 2018, when a Bitcoin frenzy occurred. The partial least squares method was used to test the proposed research model.

The results show that prudent, negative urgency, overexpectation and sensation seeking are positively associated with problematic BI behavior, while restraint is negatively associated. Problematic BI behavior is negatively related to investor well-being. Our findings also indicate that both objective and subjective financial literacy moderate the relationship between the antecedents and problematic BI behavior. Four types of investors in terms of their objective and subjective Bitcoin knowledge show different patterns in the relationship between the antecedents and problematic BI behavior.

This study offers insights for researchers by providing a deeper understanding of the contextual antecedents of problematic BI behavior and the role of financial literacy in it. This study provides detailed implications for financial institutions, policymakers, and regulators to guide rational Bitcoin investment behaviors.

This paper aims to provide an elucidative and explanatory overview of decision-making theory that human resource management and development (HR) researchers and practitioners can use to explore the impact of heuristics and biases on organizational decisions, particularly within HR contexts.

This paper draws upon three theoretical resources anchored in decision-making research: the theory of bounded rationality, the heuristics and biases program, and cognitive-experiential self-theory (CEST). A selective narrative review approach was adopted to identify, translate, and contextualize research findings that provide immense applicability, connection, and significance to the field and study of HR.

The authors extract key insights from the theoretical resources surveyed and illustrate the linkages between HR and decision-making research, presenting a theoretical framework to guide future research endeavors.

Decades of decision-making research have been distilled into a digestible and accessible framework that offers both theoretical and practical implications.

Heuristics are mental shortcuts that facilitate quick decisions by simplifying complexity and reducing effort needed to solve problems. Heuristic strategies can yield favorable outcomes, especially amid time and information constraints. However, heuristics can also introduce systematic judgment errors known as biases. Biases are pervasive within organizational settings and can lead to disastrous decisions. This paper provides HR scholars and professionals with a balanced, nuanced, and integrative framework to better understand heuristics and biases and explore their organizational impact. To that end, a forward-looking and direction-setting research agenda is presented.

Although the previous generations of the Industrial Revolution have brought many advantages to human life, scientists have been looking for a substantial breakthrough in creating technologies that can improve the quality of human life. Nowadays, we can make our factories smarter using new concepts and tools like real-time self-optimization. This study aims to take a step towards implementing key features of smart manufacturing including  preventive self-maintenance, self-scheduling and real-time decision-making.

A new bi-objective mathematical model based on Industry 4.0 to schedule received customer orders, which minimizes both the total earliness and tardiness of orders and the probability of machine failure in smart manufacturing, was presented. Moreover, four meta-heuristics, namely, the multi-objective Archimedes optimization algorithm (MOAOA), NSGA-III, multi-objective simulated annealing (MOSA) and hybrid multi-objective Archimedes optimization algorithm and non-dominated sorting genetic algorithm-III (HMOAOANSGA-III) were implemented to solve the problem. To compare the performance of meta-heuristics, some examples and metrics were presumed and solved by using the algorithms, and the performance and validation of meta-heuristics were analyzed.

The results of the procedure and a mathematical model based on Industry 4.0 policies showed that a machine performed the self-optimizing process of production scheduling and followed a preventive self-maintenance policy in real-time situations. The results of TOPSIS showed that the performances of the HMOAOANSGA-III were better in most problems. Moreover, the performance of the MOSA outweighed the performance of the MOAOA, NSGA-III and HMOAOANSGA-III if we only considered the computational times of algorithms. However, the convergence of solutions associated with the MOAOA and HMOAOANSGA-III was better than those of the NSGA-III and MOSA.

In this study, a scheduling model considering a kind of Industry 4.0 policy was defined, and a novel approach was presented, thereby performing the preventive self-maintenance and self-scheduling by every single machine. This new approach was introduced to integrate the order scheduling system using a real-time decision-making method. A new multi-objective meta-heuristic algorithm, namely, HMOAOANSGA-III, was proposed. Moreover, the crowding-distance-quality-based approach was presented to identify the best solution from the frontier, and in addition to improving the crowding-distance approach, the quality of the solutions was also considered.